Python datastructures.ImmutableDict方法代码示例

# 需要导入模块: from werkzeug import datastructures [as 别名]
# 或者: from werkzeug.datastructures import ImmutableDict [as 别名]
def obj_ref(obj):
    """Returns a tuple identifying a category/event/contrib/subcontrib"""
    from indico_livesync.models.queue import EntryType
    if isinstance(obj, Category):
        ref = {'type': EntryType.category, 'category_id': obj.id}
    elif isinstance(obj, Event):
        ref = {'type': EntryType.event, 'event_id': obj.id}
    elif isinstance(obj, Session):
        ref = {'type': EntryType.session, 'session_id': obj.id}
    elif isinstance(obj, Contribution):
        ref = {'type': EntryType.contribution, 'contrib_id': obj.id}
    elif isinstance(obj, SubContribution):
        ref = {'type': EntryType.subcontribution, 'subcontrib_id': obj.id}
    else:
        raise ValueError('Unexpected object: {}'.format(obj.__class__.__name__))
    return ImmutableDict(ref) 

# 需要导入模块: from werkzeug import datastructures [as 别名]
# 或者: from werkzeug.datastructures import ImmutableDict [as 别名]
def object_ref(self):
        """Return the reference of the changed object."""
        return ImmutableDict(type=self.type, category_id=self.category_id, event_id=self.event_id,
                             session_id=self.session_id, contrib_id=self.contrib_id, subcontrib_id=self.subcontrib_id) 

# 需要导入模块: from werkzeug import datastructures [as 别名]
# 或者: from werkzeug.datastructures import ImmutableDict [as 别名]
def run(
        self,
        requirements,
        identity=None,
        throws=None,
        on_fail=None,
        f_args=(),
        f_kwargs=ImmutableDict(),  # noqa: B008
        use_on_fail_return=True,
    ):
        """
        Used to preform a full run of the requirements and the options given,
        this method will invoke on_fail and/or throw the appropriate exception
        type. Can be passed arguments to call on_fail with via f_args (which are
        passed positionally) and f_kwargs (which are passed as keyword).

        :param requirements: The requirements to check
        :param identity: Optional. A specific identity to use for the check
        :param throws: Optional. A specific exception to throw for this check
        :param on_fail: Optional. A callback to invoke after failure,
            alternatively a value to return when failure happens
        :param f_args: Positional arguments to pass to the on_fail callback
        :param f_kwargs: Keyword arguments to pass to the on_fail callback
        :param use_on_fail_return: Boolean (default True) flag to determine
            if the return value should be used. If true, the return value
            will be considered, else failure will always progress to
            exception raising.
        """

        throws = throws or self.throws
        on_fail = _make_callable(on_fail) if on_fail is not None else self.on_fail

        if not self.fulfill(requirements, identity):
            result = on_fail(*f_args, **f_kwargs)
            if use_on_fail_return and result is not None:
                return result
            raise throws 

# 需要导入模块: from werkzeug import datastructures [as 别名]
# 或者: from werkzeug.datastructures import ImmutableDict [as 别名]
def __new__(cls, unit, qty, price, groupby, metadata):
        return _DataPointBase.__new__(
            cls,
            unit or "undefined",
            # NOTE(peschk_l): avoids floating-point issues.
            decimal.Decimal(str(qty) if isinstance(qty, float) else qty),
            decimal.Decimal(str(price) if isinstance(price, float) else price),
            datastructures.ImmutableDict(groupby),
            datastructures.ImmutableDict(metadata),
        ) 

# 需要导入模块: from werkzeug import datastructures [as 别名]
# 或者: from werkzeug.datastructures import ImmutableDict [as 别名]
def desc(self):
        output = dict(self.metadata)
        output.update(self.groupby)
        return datastructures.ImmutableDict(output) 

# 需要导入模块: from werkzeug import datastructures [as 别名]
# 或者: from werkzeug.datastructures import ImmutableDict [as 别名]
def as_dict(self, legacy=False, mutable=False):
        output = {
            "period": {"begin": self.start, "end": self.end},
            "usage": {
                key: [v.as_dict(legacy=legacy, mutable=mutable) for v in val]
                for key, val in self._usage.items()
            },
        }
        return output if mutable else datastructures.ImmutableDict(output) 

# 需要导入模块: from werkzeug import datastructures [as 别名]
# 或者: from werkzeug.datastructures import ImmutableDict [as 别名]
def test_as_dict_immutable(self):
        point_dict = dataframe.DataPoint(**self.default_params).as_dict()
        self.assertIsInstance(point_dict, datastructures.ImmutableDict)
        self.assertEqual(dict(point_dict), {
            "vol": {"unit": "undefined", "qty": decimal.Decimal(0)},
            "rating": {"price": decimal.Decimal(0)},
            "groupby": {},
            "metadata": {},
        }) 

# 需要导入模块: from werkzeug import datastructures [as 别名]
# 或者: from werkzeug.datastructures import ImmutableDict [as 别名]
def test_default_converters(self):
        class MyMap(r.Map):
            default_converters = r.Map.default_converters.copy()
            default_converters['foo'] = r.UnicodeConverter
        assert isinstance(r.Map.default_converters, ImmutableDict)
        m = MyMap([
            r.Rule('/a/<foo:a>', endpoint='a'),
            r.Rule('/b/<foo:b>', endpoint='b'),
            r.Rule('/c/<c>', endpoint='c')
        ], converters={'bar': r.UnicodeConverter})
        a = m.bind('example.org', '/')
        assert a.match('/a/1') == ('a', {'a': '1'})
        assert a.match('/b/2') == ('b', {'b': '2'})
        assert a.match('/c/3') == ('c', {'c': '3'})
        assert 'foo' not in r.Map.default_converters